Detecting deviations from randomness

Jiaying Zhao, Princeton University

Daniel Osherson, Princeton University

Abstract

We explore the ability to distinguish random from non-random
events without invoking the randomness concept. Randomness is defined in terms of
radioactive decay whereas non-randomness is quantified by excess repetitions
(i.e., repeat) or alternations between successive bits (i.e., switch). In four
experiments, participants completed tasks including identifying the boundary
between random and non-random textures, distinguishing random from non-random
movement, learning to classify patterns, and tracking changes in successive
matrices. Importantly, in task instructions, no mention was made of randomness,
probability, or related concepts. We found superior performance in distinguishing
random stimuli from repeat stimuli compared to switch stimuli. Moreover, memory
for repeat stimuli declined as stimuli became more random, whereas memory for
switch stimuli did not vary with the degree of non-randomness.